Discover Awesome MCP Servers

click-mcp

Convierte CLIs de click en servidores MCP con una línea de código.

NASA MCP Server

Provides standardized access to 20+ NASA data sources including astronomy pictures, Mars rover photos, near-Earth objects, satellite imagery, space weather, and planetary data through a unified interface optimized for AI consumption.

ClickHouse Cloud API MCP Server

A Multi-Agent Conversation Protocol server that enables interaction with the ClickHouse Cloud API, providing programmatic access to ClickHouse Cloud services through natural language.

Docker Server Manager Go MCP

This looks like a combination of words and abbreviations related to Docker and potentially a project name. Here's a possible translation, depending on the context: **Possible Translations:** * **Direct Translation (Literal):** Administrador de Servidor Docker Go MCP (This is a very literal translation and might not be the best.) * **More Natural Translation (Assuming it's a project):** Administrador de Servidores Docker (Go MCP) (This separates the core functionality from what might be a project name or identifier.) * **If "MCP" is an acronym:** Administrador de Servidores Docker (Go, *[Acrónimo de MCP]*) (Replace "*[Acrónimo de MCP]*" with the actual meaning of the acronym if you know it.) **Explanation of the parts:** * **dockerServerManager:** Administrador de Servidores Docker (Docker Server Manager) * **Go:** Go (Refers to the Go programming language) * **MCP:** This is unclear without more context. It could be: * Part of a project name. * An acronym for something specific to the project. **Therefore, to give you the best translation, I need more context. What is "dockerServerMangerGoMCP" referring to? Is it a project name? Do you know what "MCP" stands for?**

Vertica MCP Server

A Model Context Protocol server that enables AI assistants to interact with Vertica databases through SQL queries, schema inspection, database documentation, and data export capabilities.

discord-mcp

MCP server with over 70 tools to manage and maintain an entire Discord server.

VA Form Generation MCP Server

Provides tools for auditing and fixing scaffolded VA forms to ensure they follow best practices and VA.gov content standards. Enables automated validation, agent prompt generation, and orchestration of form fixes across any vets-website workspace.

Resemble AI Voice Generation MCP Server

Se integra con Claude y Cursor utilizando el Protocolo de Contexto del Modelo para generar audio de voz a partir de texto utilizando las voces de Resemble AI.

MCP Hub

An Express server implementation of Model Context Protocol that allows websites to connect to LLMs through streamable HTTP and stdio transports, with a built-in chat UI for testing responses.

webdev-mcp

An MCP server that provides web development tools including taking screenshots of screens, enabling AI agents to capture and analyze visual content during development.

TypeScript MCP Server Boilerplate

A boilerplate project for quickly developing Model Context Protocol servers using TypeScript, featuring example tools (calculator, greeting) and resources (server info) with Zod schema validation.

MySQL MCP Server Pro

Provides comprehensive MySQL database operations including CRUD, performance optimization, health analysis, and anomaly detection. Supports multiple connection modes, OAuth2.0 authentication, and role-based permissions for database management through natural language.

Playwright MCP Server

A minimal server that exposes Playwright browser automation capabilities through a simple API, enabling webpage interaction, DOM manipulation, and content extraction via the Model Context Protocol.

MCP Home Assistant

Enables natural language control of Home Assistant smart home devices through Cursor AI, supporting entity queries, automation management, configuration file editing, and system operations.

Uni-res_MCP

An MCP server for my University Results

Ziwei Astrology MCP Server

Enables generation of detailed Chinese Ziwei Doushu (Purple Star) astrological charts with geographic location support and true solar time conversion. Provides tools for geocoding locations, converting Beijing time to apparent solar time, and creating comprehensive astrology readings based on birth information.

AI MCP ServiceNow

A Model Context Protocol server that integrates with ServiceNow instances, allowing users to utilize AI tools within ServiceNow without writing code.

Argo Workflow MCP Server

Enables AI agents to manage Argo Workflows through REST API, supporting workflow template and instance operations including creation, submission, monitoring, and deletion with token authentication.

mcp-flyin

A server that handles messaging or commands over a custom protocol

Azure Model Context Protocol (MCP) Hub

Okay, here are some resources, tools, and potential starting points for building and integrating Model Context Protocol (MCP) servers on Azure using multiple languages. Keep in mind that MCP is relatively new, so the ecosystem is still developing. I'll focus on providing general guidance and tools that can be adapted. **Understanding Model Context Protocol (MCP)** Before diving into specific languages, make sure you have a solid understanding of MCP itself. Key aspects include: * **Purpose:** MCP aims to standardize the way models receive contextual information, making it easier to integrate models into various applications and workflows. * **Protocol:** It defines a standard interface for providing context to models, typically using HTTP or gRPC. * **Context:** This includes data, metadata, and other relevant information that helps the model make better predictions or decisions. **General Azure Resources & Tools (Language Agnostic)** These resources are useful regardless of the programming language you choose: * **Azure App Service:** A platform-as-a-service (PaaS) for hosting web applications, including MCP servers. It supports multiple languages (Node.js, Python, Java, .NET, etc.). [https://azure.microsoft.com/en-us/services/app-service/](https://azure.microsoft.com/en-us/services/app-service/) * **Azure Functions:** A serverless compute service that allows you to run code without managing servers. Ideal for smaller MCP server implementations or specific context providers. Supports multiple languages. [https://azure.microsoft.com/en-us/services/functions/](https://azure.microsoft.com/en-us/services/functions/) * **Azure Kubernetes Service (AKS):** A managed Kubernetes service for deploying and managing containerized applications, including MCP servers. Provides maximum flexibility and scalability. [https://azure.microsoft.com/en-us/services/kubernetes-service/](https://azure.microsoft.com/en-us/services/kubernetes-service/) * **Azure API Management:** A fully managed service that enables you to publish, secure, transform, monitor, and manage APIs. Useful for exposing your MCP server as a well-defined API. [https://azure.microsoft.com/en-us/services/api-management/](https://azure.microsoft.com/en-us/services/api-management/) * **Azure Container Registry (ACR):** A private registry for storing and managing container images. Essential if you're using AKS or deploying containerized MCP servers. [https://azure.microsoft.com/en-us/services/container-registry/](https://azure.microsoft.com/en-us/services/container-registry/) * **Azure Monitor:** Collects and analyzes telemetry data from your Azure resources, including your MCP servers. Helps you monitor performance, identify issues, and gain insights. [https://azure.microsoft.com/en-us/services/monitor/](https://azure.microsoft.com/en-us/services/monitor/) * **Azure Key Vault:** A secure store for secrets, keys, and certificates. Use it to protect sensitive information used by your MCP server. [https://azure.microsoft.com/en-us/services/key-vault/](https://azure.microsoft.com/en-us/services/key-vault/) **Language-Specific Guidance & Examples** Since MCP is a protocol, you can implement it in various languages. Here's a breakdown with potential approaches: **1. Python** * **Frameworks:** * **Flask:** A lightweight web framework for building APIs. Easy to learn and use. * **FastAPI:** A modern, high-performance web framework for building APIs with Python 3.6+ based on standard Python type hints. Excellent for data validation and serialization. * **gRPC (Python):** If MCP uses gRPC, use the `grpcio` package. * **Libraries:** * `requests`: For making HTTP requests to other services. * `pydantic`: For data validation and serialization. * `azure-identity`, `azure-storage-blob`, etc.: Azure SDKs for accessing other Azure services. * **Example (Conceptual - Flask):** ```python from flask import Flask, request, jsonify import json app = Flask(__name__) @app.route('/context', methods=['POST']) def provide_context(): try: data = request.get_json() # Get the request body as JSON # Process the data (context request) # ... your logic to fetch or generate context ... context_data = {"relevant_info": "example context", "source": "my_context_provider"} # Example context return jsonify(context_data), 200 # Return the context as JSON except Exception as e: return jsonify({"error": str(e)}), 500 if __name__ == '__main__': app.run(debug=True, host='0.0.0.0', port=80) ``` * **Deployment:** Deploy to Azure App Service, Azure Functions (using a custom handler), or AKS (using a Docker container). **2. Node.js (JavaScript/TypeScript)** * **Frameworks:** * **Express.js:** A popular web framework for Node.js. * **NestJS:** A framework for building efficient, scalable Node.js server-side applications. Uses TypeScript. * **gRPC (Node.js):** If MCP uses gRPC, use the `@grpc/grpc-js` package. * **Libraries:** * `axios`: For making HTTP requests. * `body-parser`: For parsing request bodies. * `@azure/identity`, `@azure/storage-blob`, etc.: Azure SDKs. * **Example (Conceptual - Express.js):** ```javascript const express = require('express'); const bodyParser = require('body-parser'); const app = express(); const port = 80; app.use(bodyParser.json()); app.post('/context', (req, res) => { try { const requestData = req.body; // Process the requestData (context request) // ... your logic to fetch or generate context ... const contextData = { relevant_info: "example context", source: "my_context_provider" }; res.json(contextData); } catch (error) { console.error(error); res.status(500).json({ error: error.message }); } }); app.listen(port, () => { console.log(`Server listening at http://localhost:${port}`); }); ``` * **Deployment:** Deploy to Azure App Service, Azure Functions, or AKS. **3. Java** * **Frameworks:** * **Spring Boot:** A popular framework for building Java applications, including REST APIs. * **Micronaut:** A modern, full-stack framework for building modular, easily testable microservice applications. * **gRPC (Java):** If MCP uses gRPC, use the `io.grpc` libraries. * **Libraries:** * `RestTemplate` (Spring): For making HTTP requests. * `azure-identity`, `azure-storage-blob`, etc.: Azure SDKs. * **Example (Conceptual - Spring Boot):** ```java import org.springframework.boot.SpringApplication; import org.springframework.boot.autoconfigure.SpringBootApplication; import org.springframework.web.bind.annotation.PostMapping; import org.springframework.web.bind.annotation.RequestBody; import org.springframework.web.bind.annotation.RestController; import java.util.Map; import java.util.HashMap; @SpringBootApplication @RestController public class ContextProviderApplication { public static void main(String[] args) { SpringApplication.run(ContextProviderApplication.class, args); } @PostMapping("/context") public Map<String, String> provideContext(@RequestBody Map<String, Object> requestData) { // Process the requestData (context request) // ... your logic to fetch or generate context ... Map<String, String> contextData = new HashMap<>(); contextData.put("relevant_info", "example context"); contextData.put("source", "my_context_provider"); return contextData; } } ``` * **Deployment:** Deploy to Azure App Service, Azure Functions (using a custom handler), or AKS. **4. .NET (C#)** * **Frameworks:** * **ASP.NET Core:** A cross-platform, high-performance framework for building web APIs. * **gRPC (.NET):** If MCP uses gRPC, use the `Grpc.AspNetCore` package. * **Libraries:** * `HttpClient`: For making HTTP requests. * `Azure.Identity`, `Azure.Storage.Blobs`, etc.: Azure SDKs. * **Example (Conceptual - ASP.NET Core):** ```csharp using Microsoft.AspNetCore.Mvc; using System.Collections.Generic; namespace ContextProvider.Controllers { [ApiController] [Route("[controller]")] public class ContextController : ControllerBase { [HttpPost("/context")] public ActionResult<Dictionary<string, string>> ProvideContext([FromBody] Dictionary<string, object> requestData) { // Process the requestData (context request) // ... your logic to fetch or generate context ... var contextData = new Dictionary<string, string> { { "relevant_info", "example context" }, { "source", "my_context_provider" } }; return contextData; } } } ``` * **Deployment:** Deploy to Azure App Service, Azure Functions, or AKS. **Key Considerations for Implementation** * **Data Format:** Determine the data format for the context (JSON, Protobuf, etc.) and use appropriate libraries for serialization and deserialization. * **Authentication/Authorization:** Secure your MCP server using Azure Active Directory (Azure AD) or other authentication mechanisms. * **Error Handling:** Implement robust error handling and logging. * **Scalability:** Design your MCP server to handle the expected load. Consider using caching, load balancing, and autoscaling. * **Monitoring:** Use Azure Monitor to track the performance and health of your MCP server. * **Context Sources:** Identify the sources of context data (databases, APIs, files, etc.) and implement the logic to retrieve and transform the data. * **MCP Specification:** Carefully review the MCP specification (if available) to ensure your implementation is compliant. If there isn't a formal specification, work with the model providers to define a clear contract. * **gRPC vs. REST:** Decide whether to use gRPC or REST (HTTP) for your MCP server. gRPC is generally more efficient for high-performance scenarios, but REST is often simpler to implement. **Steps to Get Started** 1. **Choose a Language:** Select the language you're most comfortable with or that best fits your requirements. 2. **Set up Azure Resources:** Create an Azure account and provision the necessary resources (App Service, Functions, AKS, etc.). 3. **Implement the MCP Server:** Write the code to handle context requests, retrieve context data, and return it in the appropriate format. 4. **Deploy to Azure:** Deploy your MCP server to Azure. 5. **Test and Monitor:** Thoroughly test your MCP server and monitor its performance. **Important Notes:** * **MCP is Evolving:** The Model Context Protocol is a relatively new concept, so the specific details and best practices may change over time. Stay up-to-date with the latest developments. * **No Official Azure MCP SDK:** As of now, there isn't a dedicated Azure SDK specifically for MCP. You'll need to use general-purpose web frameworks and Azure SDKs to implement the protocol. * **Focus on the Interface:** The key is to implement the MCP interface correctly, regardless of the underlying language or framework. I hope this comprehensive guide helps you get started with building and integrating MCP servers on Azure! Let me know if you have any more specific questions.

macOS MCP Servers

Enables Claude Desktop and GitHub Copilot to interact with native macOS applications including Spotify, Apple Music, Notes, Calendar, FaceTime, and Contacts through natural language commands. Provides comprehensive control over music playback, note management, calendar events, video calls, and contact operations using AppleScript integration.

ClinicalTrials.gov MCP Server

Empowers AI agents with direct access to the official ClinicalTrials.gov database, enabling programmatic searching, retrieval, and analysis of clinical study data through a Model Context Protocol interface.

Expo Docs MCP Server

Enables AI-powered semantic search through Expo SDK documentation across multiple versions (v51-v53 and latest), allowing developers to quickly find relevant documentation with configurable similarity scoring.

Weather MCP Server

Connects Claude Desktop to the Open-Meteo API to retrieve real-time weather data for cities worldwide without requiring an API key.

mcp-servers-experiments

Este repositorio contiene mis experimentos con servidores MCP.

MCP RAG Server

Enables retrieval-augmented generation (RAG) by indexing and searching through documents (Markdown, text, PowerPoint, PDF) using vector embeddings with multilingual-e5-large model and PostgreSQL pgvector. Supports contextual chunk retrieval and incremental indexing for efficient document management.

P-Link-MCP

Payment & Transaction Tools that allow AI agents to send, receive, and request payments

Charts Visualization MCP Server

Enables generation and visualization of bar and pie charts from structured data using FastAPI and Altair. Charts are saved as PNG images and served via REST API endpoints with unique URLs.

ms-365-mcp-server

Microsoft 365 MCP Server